I helped Jenny 8. Lee, Chrys Wu and Stephanie Pereira organize the event. Then I joined a team working with digital heaps of NYC taxi trip data to make data visualizations and start some other projects. My favorite one is here (with a detail below), which is a representation of taxi usage for 24 hours, set around a clock. Beautiful. It was built by Zoe Fraade-Blanar using Processing and data crunched by the other teammates.

Click image for full view

I came away from the event with many new connections, excitement about learning Processing, some more skills in Sinatra and a note to check out Bees with Machine Guns(!)

Check out the great writeup of the day for a summary of the event. Personally, I worked on recrafting some Associated Press Election data for a project we're working on at WNYC. I also had conversations that could lead to several collaborations, and even got some tips for programming in Ruby and Sinatra.

For two, we're welcoming voters to share their experiences with the ballot via text. They (or you!) sign up by texting BALLOT to 30644.

Video Fun

The whole thing started when our host Brian Lehrer and reporter Azi Paybarah actually tried the sample ballot and made several mistakes. Which leads me to the third component: A video about using the new ballot:

My preso will likely be the lowest-tech of the bunch. Our aim was, and is, to connect journalists and citizen-sources using basic text messages, and our method was brainstorming, learning and prototyping in two neighborhoods -- Southwest Detroit and Miami's Little Haiti. We absorbed a ton. (And we sparked an investigative series on illegal truck traffic.)

There are certainly opportunities here to mash up APIs and build on some nifty platforms. I'll talk about that, too. But as we continue working toward connecting with sources via texting, some of our best insights have come from coffee shop conversations, church bulletin announcements and short-codes scrawled on sidewalks.

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What's so exceptional about the journalism innovation award The Takeaway won yesterday is that it's not for a broadcast, a series or a blog post.

It's for an experiment.

"Sourcing Through Texting" has been a process of immersion, exploration and rapid prototyping. Journalists and community leaders spend time in a neighborhood focusing on a simple question: How might reporters and citizen-sources make better connections through texting?

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Today our education reporter had a bunch of data from New York State she was trying to match to schools in New York City. But the school codes used by the two governments look radically different.

For example, PS 15 on the Lower East Side is known to the state as 310100010015; the city calls it 01M015.

I once made a nifty formula to make the conversion(!), but a more straightforward and official approach involves the Excel spreadsheet found here. It lists all of the city schools, along with their addresses, various codes, and more. For a data cruncher, that's a secret decoder ring.

What made me smile was that the only reason I knew this document even existed was because of a little prototype I tried during the first swine flu outbreak. That experiment wasn't robust enough to make it beyond this blog, but it taught me a lot ... including where to find this ring!

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What a great visualization of Netflix movie-rental data from the New York Times! Love how you can see how different movies play across the city.

It's even more interesting when you know something about the demographic makeup of the zip codes. Look how the Harlem River between upper Manhattan and the South Bronx is a bright dividing line for almost every movie.

How about a mashup that would reflect this info and demographic data simultaneously?

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John Keefe

Adventures in journalism-doing, mapmaking, code mangling and hardware hacking.
Much of what I do is for WNYC's Data News Team, and I'm one of the DIY co-conspirators on Team Blinky. Opinions here are mine alone.